Neuromorphic Device Based on Material and Device Innovation toward Multimode and Multifunction
In the era of big data, multimodal and multifunctional neuromorphic devices offer significant opportunities in designing AI hardware. In this work, recent advances about emerging material systems and novel device structures in this field are summarized in detail. Potential applications are reviewed.
Feng Guo +3 more
wiley +1 more source
AI-embedded IoT healthcare optimization with trust-aware mobile edge computing. [PDF]
Alamri M +3 more
europepmc +1 more source
Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 more
wiley +1 more source
Federated learning with LSTM and error correcting codes for secure and private identification of IoT devices. [PDF]
Alshaya SA.
europepmc +1 more source
Speech Recognition with Cochlea‐Inspired In‐Sensor Computing
Traditional speech recognition methods rely on software‐based feature extraction that introduces latency and high energy costs, making them unsuitable for low‐power devices. A proof‐of‐concept demonstration is provided of a bioinspired tonotopic sensor for speech recognition that mimics the human cochlea, using a spiral‐shaped elastic metamaterial. The
Paolo H. Beoletto +4 more
wiley +1 more source
Cybersecure Intelligent Sensor Framework for Smart Buildings: AI-Based Intrusion Detection and Resilience Against IoT Attacks. [PDF]
Siam MA +6 more
europepmc +1 more source
Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context
Agribusiness, EarlyView.
Alexis H. Villacis
wiley +1 more source
Securing Generative Artificial Intelligence with Parallel Magnetic Tunnel Junction True Randomness
True random numbers can protect generative artificial intelligence (GAI) models from attacks. A highly parallel, spin‐transfer torque magnetic tunnel junction‐based system is demonstrated that generates high‐quality, energy‐efficient random numbers.
Youwei Bao, Shuhan Yang, Hyunsoo Yang
wiley +1 more source

